This project is focused on developing a deep learning based data acquisition and analytics tool using vision-based sensors (i.e., cameras)...
Read MoreDr. Jingqin Gao is a dedicated professional with over 10 years of experience in transportation planning and engineering. She has served as principal investigator (PI), co-PI, and lead researcher for multiple projects funded by the U.S. DOT, NASEM, AASHTO, NYSDOT, NYCDOT, and NJDOT. As the Assistant Director of Research at C2SMART University Transportation Center funded by the U.S. Department of Transportation (USDOT). Dr. Gao assisted the center to secure a $15M grant, including $10M from U.S. DOT, to pursue a research and educational program focused on understanding and combatting traffic congestion. Dr. Gao’s research has focused on emerging technologies and urban analytics for smart transportation. She is best known for her research on evaluating the field performance of U.S. DOT Connected Vehicle Pilot Deployment Safety Applications in New York City, utilizing cooperative automated transportation data for transportation operational strategies, assessing the mobility and policy impacts on transportation systems during COVID-19, AI-based transportation solutions for smart cities, and double parking analysis.
Before joining NYU, Dr. Gao worked in the Modeling and Data Analysis unit at the New York City Department of Transportation (NYCDOT), which supports the agency’s internal planning, technical review processes, and coordinated with external agencies on regional projects.
Beyond her academic pursuits, she champions women in STEM, diversity, equity, and workforce development. Dr. Gao is named as Who’s Who America in Professional Women in 2023 and is a recipient of the Dr. Louis J. Pignataro Memorial Transportation Education Award by ITE MET section and National Leadership Legacy Award from the WTS-GNY chapter.
C2SMART Projects
COVID-19’s Effect on Transportation: Developing a Public COVID-19 Data Dashboard
The COVID-19 outbreak has dramatically changed travel behavior in cities across the world. With changed travel demand, economic activity, and...
Read MoreAlgorithms to Convert Basic Safety Messages into Traffic Measures
An NSF project named “study of driving volatility in connected and cooperative vehicle systems” aims at extracting driving volatility, characterized...
Read MoreUnderstanding and Enabling Cooperative Driving in New York City: A Data-driven Approach
The NYCDOT Team (NYCDOT and C2SMART) will assist the USDOT in understanding and enabling Cooperative Driving for Advanced Connected Vehicles...
Read MoreNJDOT Bridge Resource Program
The primary mission of the Bridge Resource Program (BRP) is to provide ongoing engineering evaluation and research support to the...
Read MoreITS Deployment Evaluation Program Technical and Program Support
C2SMART researchers are working in partnership with Noblis to provide technical and management support for the ITS Deployment Evaluation program...
Read MoreUtilizing CAT Data for Freeway Operational Strategies
The overall scope of the project is to assess use cases where freeway operations strategies could be improved through the...
Read MoreC2SMART-NYCDOT Connected Vehicle Research Breaks New Ground To Improve Mobility and Ensure Accessibility For Pedestrians with Vision Disabilities in NYC
As part of USDOT's Connected Vehicle Project, C2SMART researchers at New York University – in collaboration with NYCDOT and industry...
Read MoreResearch on Concrete Applications for Sustainable Transportation (RE-CAST)
This project has many parts, and the NYU team is currently working with Rutgers on the RE-CAST 2D subproject. This...
Read MoreNew York City Connected Vehicle Pilot
Researchers at NYU are working with NYCDOT and other partners on this portion of the NYC CV Pilot, as well...
Read MoreEvaluation of New Features at MTA New York City Transit’s Accessible Station Lab
C2SMART researchers are working under the direction of NYCT staff in administering surveys/conducting interviews and collecting data from users of...
Read MoreStatewide Open Source Advanced Traffic Management System (ATMS) Software Research and Pilot
This project’s goal is to research, evaluate and test the ability and effectiveness of using open source ATMS software to...
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